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The Patient Repository for EEG Data + Computational Tools (PRED+CT)
Electroencephalographic (EEG) recordings are thought to reflect the network-wide operations of canonical neural computations, making them a uniquely insightful measure of brain function. As evidence of these virtues, numerous candidate biomarkers of different psychiatric and neurological diseases ha...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702317/ https://www.ncbi.nlm.nih.gov/pubmed/29209195 http://dx.doi.org/10.3389/fninf.2017.00067 |
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author | Cavanagh, James F. Napolitano, Arthur Wu, Christopher Mueen, Abdullah |
author_facet | Cavanagh, James F. Napolitano, Arthur Wu, Christopher Mueen, Abdullah |
author_sort | Cavanagh, James F. |
collection | PubMed |
description | Electroencephalographic (EEG) recordings are thought to reflect the network-wide operations of canonical neural computations, making them a uniquely insightful measure of brain function. As evidence of these virtues, numerous candidate biomarkers of different psychiatric and neurological diseases have been advanced. Presumably, we would only need to apply powerful machine-learning methods to validate these ideas and provide novel clinical tools. Yet, the reality of this advancement is more complex: the scale of data required for robust and reliable identification of a clinical biomarker transcends the ability of any single laboratory. To surmount this logistical hurdle, collective action and transparent methods are required. Here we introduce the Patient Repository of EEG Data + Computational Tools (PRED+CT: predictsite.com). The ultimate goal of this project is to host a multitude of available tasks, patient datasets, and analytic tools, facilitating large-scale data mining. We hope that successful completion of this aim will lead to the development of novel EEG biomarkers for differentiating populations of neurological and psychiatric disorders. |
format | Online Article Text |
id | pubmed-5702317 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57023172017-12-05 The Patient Repository for EEG Data + Computational Tools (PRED+CT) Cavanagh, James F. Napolitano, Arthur Wu, Christopher Mueen, Abdullah Front Neuroinform Neuroscience Electroencephalographic (EEG) recordings are thought to reflect the network-wide operations of canonical neural computations, making them a uniquely insightful measure of brain function. As evidence of these virtues, numerous candidate biomarkers of different psychiatric and neurological diseases have been advanced. Presumably, we would only need to apply powerful machine-learning methods to validate these ideas and provide novel clinical tools. Yet, the reality of this advancement is more complex: the scale of data required for robust and reliable identification of a clinical biomarker transcends the ability of any single laboratory. To surmount this logistical hurdle, collective action and transparent methods are required. Here we introduce the Patient Repository of EEG Data + Computational Tools (PRED+CT: predictsite.com). The ultimate goal of this project is to host a multitude of available tasks, patient datasets, and analytic tools, facilitating large-scale data mining. We hope that successful completion of this aim will lead to the development of novel EEG biomarkers for differentiating populations of neurological and psychiatric disorders. Frontiers Media S.A. 2017-11-21 /pmc/articles/PMC5702317/ /pubmed/29209195 http://dx.doi.org/10.3389/fninf.2017.00067 Text en Copyright © 2017 Cavanagh, Napolitano, Wu and Mueen. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Cavanagh, James F. Napolitano, Arthur Wu, Christopher Mueen, Abdullah The Patient Repository for EEG Data + Computational Tools (PRED+CT) |
title | The Patient Repository for EEG Data + Computational Tools (PRED+CT) |
title_full | The Patient Repository for EEG Data + Computational Tools (PRED+CT) |
title_fullStr | The Patient Repository for EEG Data + Computational Tools (PRED+CT) |
title_full_unstemmed | The Patient Repository for EEG Data + Computational Tools (PRED+CT) |
title_short | The Patient Repository for EEG Data + Computational Tools (PRED+CT) |
title_sort | patient repository for eeg data + computational tools (pred+ct) |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702317/ https://www.ncbi.nlm.nih.gov/pubmed/29209195 http://dx.doi.org/10.3389/fninf.2017.00067 |
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